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Autor/inn/enAndrade, Stefan Bastholm; Andersen, Ditte
TitelDigital Story Grammar: A Quantitative Methodology for Narrative Analysis
QuelleIn: International Journal of Social Research Methodology, 23 (2020) 4, S.405-421 (17 Seiten)
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ZusatzinformationORCID (Andrade, Stefan Bastholm)
ORCID (Andersen, Ditte)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1364-5579
DOI10.1080/13645579.2020.1723205
SchlagwörterPersonal Narratives; Discourse Analysis; Social Structure; Verbs; Form Classes (Languages); Content Analysis; Information Technology; Research Methodology; Social Science Research; Foreign Countries; Late Adolescents; United Kingdom
AbstractDigital story grammar (DSG) is a methodology that combines narrative theory and computerised text analysis. The methodology offers new ways of identifying patterns in narrative identity work and examining how these patterns relate to social structures such as gender and social class. DSG works through an algorithm that identifies narrative units consisting of subjects, verbs and objects. To demonstrate the potential of the methodology, we apply it to interviews with young people from the "Timescapes Qualitative Longitudinal Data Archive" and address four research questions: "Who" are in the young people's stories (characters)? "What" are their narratives about (domains of experiences)? "When" do they taking place (temporality)? "How" are the narratives told (sense of agency)? Among other findings, we observed that young people with middle-class backgrounds convey a stronger sense of agency than their working-class peers, and we show how this correlates with the ways in which they navigate school-to-work trajectories. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2022/1/01
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